Food-borne disease remains a substantial burden on the public health. It is estimated that each year roughly 1 in 6 Americans (or 48 million people) get sick, 128,000 are hospitalized, and 3,000 die of foodborne diseases. See CDC. Estimating Foodborne Illness: An Overview (2014). Nontyphoidal Salmonella enterica and Escherichia coli 0157:H7 include two of the top pathogens contributing to domestically acquired foodborne illnesses resulting in hospitalization. Pathogen prevalence in food varies significantly. For example, the percentage of Salmonella-positive birds and fecal samples on farms has ranged from 5 to 100% (Foley, S. L., et al., J Anim Sci, 2008. 86(14 Suppl): p. E149-62), and 3 to 17% of pathogen-positive products can be found on fresh produce on farms (Strawn, L. K., et al., Applied and Environmental Microbiology, 2013. 79(2): p. 588-600).
Food production practices have developed many intervention strategies including the physical and chemical methods to reduce the contamination from the well-recognized food-borne pathogens such as S. enterica and E. coli. In order to maintain control of our food production system, the ability to rapidly detect the presence of viable pathogens along the production chain is essential for determining intervention and control strategies.
Current rapid approaches based on the immunoassays or nucleic acid detection assays are unable to distinguish between viable and non-viable pathogens (without an enrichment step) as most production processes have the inherent ability to provide some control. One key point in this is identifying the presence of live pathogens along the processing chain to evaluate risk and institute corrective measures.
Ethidium monoazide (EMA) and propidium monoazide (PMA) have been used to prevent the DNA amplification from the dead bacterial cells. They specifically permeate dead cells and irreversibly attach covalently to the DNA to prevent amplification. See, e.g., Yang, X., et al., Food Microbiology, 2011. 28(8): p. 1478-1482; Melero, B., et al., Food Microbiology, 2011. 28(7): p. 1353-1358; Taskin, B., A. et al., Appl. Environ. Microbiol., 2011. 77(13): p. 4329-4335; Chen, S., et al., Appl. Environ. Microbiol., 2011. 77(12): p. 4008-4016; Liang, N., et al., Journal of Food Science, 2011. 76(4): p. M234-M237. However, the degree of deactivation is limited to the presence of no more than 103 dead cells in the PCR. See, e.g., Soejima, T., Analytical Biochemistry, 2011. 418(2): p. 286-294. Reverse transcriptase PCR (RT-PCR) was adapted to detect the less environmentally stable messenger RNA (mRNA) in bacteria so live cells detection can be achieved. See, e.g., Martínez-Blanch, J., et al., European Food Research and Technology, 2011. 232(6): p. 951-955; Cobo Molinos, A., et al., Current Microbiology, 2010. 61(6): p. 515-519. However, costs, complexities, and other technical issues have made neither a routine diagnostic tool.
Fluorescence microscope and flow cytometry have also been used to distinguish the viable cells from the dead cells. These methods utilize a fluorescent dye exclusion method to evaluate cell viability. Typical viability dyes are excluded by viable cells but can penetrate damaged cell membranes of dead cells and emit fluorescence upon binding to nucleic acid inside these cells. Single cell analysis of cell viability and MP typically has relied on staining procedures with fluorescence dyes. However, usage of fluorescence dyes with bacteria is not simple. Due to large interspecies variation, staining and measurement protocols have to be developed separately for every bacterial species to ensure qualitative and quantitative high level results. See, e.g., David, F., et al., Biotechnology and Bioengineering, 2012. 109(2): p. 483-492. In addition, some cells may be still structurally intact though dead (e.g., after being killed with UV light and antibiotics). See, e.g., Trevors, J. T., Journal of Microbiological Methods, 2012. 90(1): p. 25-28; Soejima, T., et al., Biochimica et Biophysica Acta (BBA)—General Subjects, 2012. 1820(12): p. 1980-1986. Moreover, some cells with injured cell membrane may repair and retain viability. See, e.g., Corrotte, M., et al., Traffic, 2012. 13(3): p. 483-494; Soejima, T., et al., FEMS Microbiology Letters, 2009. 294(1): p. 74-81. ENREF 19 Therefore, assays based on the cell membrane integrity may not be accurate enough to differentiate live from dead cells.
Separations of viable cells from the dead population have also been explored using dielectrophoresis, defined as the motion of polarizable particles exposed to a non-uniform electric field. See, e.g., Lapizco-Encinas, B. H., et al., Analytical Chemistry, 2004. 76(6): p. 1571-1579; van den Driesche, S., et al., Sensors and Actuators B: Chemical, 2012. 170(0): p. 207-214; van den Driesche, S., et al., Procedia Engineering, 2011. 25(0): p. 705-708. ENREF 17 The separation is based on the difference in cell membrane conductivity. The conductivity of viable cell membranes tends to be 10−4 μS/mm. When a cell dies, the cell membrane becomes permeable, and its conductivity can increase by a factor of 104. See, e.g., Lapizco-Encinas, B. H., et al., Analytical Chemistry, 2004. 76(6): p. 1571-1579. This method again is based on the cell membrane integrity, which could generate false signal from the structurally intact but dead cells.
As such, the food processing industry is interested in technologies or methods that can quickly and accurately detect viable (live) bacteria, as these are the pathogens that can cause illness. Common foodborne pathogen screening methods like PCR (polymerase chain reaction) use DNA-based methods to perform the detection. However, because both viable (live) and non-viable (dead) bacteria contain the same DNA and other properties, it is difficult to distinguish between them without performing additional time-consuming incubation and culturing steps.
It is with respect to these and other considerations that the various embodiments described below are presented.